公开(公告)号：US20230266221A1

公开(公告)日：2023-08-24

申请号：US18041086

申请日：2021-08-11

Applicant: ALLEN INSTITUTE

Inventor： Gregory JOHNSON ,  Chawin OUNKOMOL ,  Forrest COLLMAN ,  Sharmishtaa SESHAMANI ,  Michael KRANDA

IPC: G01N15/02 ,  G01N15/14

CPC classification number: G01N15/0227 ,  G01N15/1429 ,  G01N15/1475 ,  G01N2015/1445

Abstract: The present invention provides various methods for easily assessing cell quality of a cell production process, suitably using non-invasive visual methods and neural networks for generating predictive fluorescence images of cells to assess quality attributes. Also provided are systems and methods for carrying out such processes.

公开(公告)号：US20210173188A1

公开(公告)日：2021-06-10

申请号：US17148192

申请日：2021-01-13

Applicant: ALLEN INSTITUTE

Inventor： Gregory JOHNSON ,  Chawin OUNKOMOL ,  Forrest COLLMAN ,  Sharmishtaa SESHAMANI

IPC: G02B21/00 ,  G06N3/08 ,  G06N20/20 ,  G06T7/11 ,  G06T7/187 ,  G06T7/174 ,  G06N3/04

Abstract: A computing device, method, system, and instructions in a non-transitory computer-readable medium for performing image analysis on 3D microscopy images to predict localization and/or labeling of various structures or objects of interest, by predicting the location in such images at which a dye or other marker associated with such structures would appear. The computing device, method, and system receives sets of 3D images that include unlabeled images, such as transmitted light images or electron microscope images, and labeled images, such as images captured with fluorescence tagging. The computing device trains a statistical model to associate structures in the labeled images with the same structures in the unlabeled light images. The processor further applies the statistical model to a new unlabeled image to generate a predictive labeled image that predicts the location of a structure of interest in the new image.

公开(公告)号：US20190384047A1

公开(公告)日：2019-12-19

申请号：US16304021

申请日：2018-08-08

Applicant: ALLEN INSTITUTE

Inventor： Gregory JOHNSON ,  Chawin OUNKOMOL ,  Forrest COLLMAN ,  Sharmishtaa SESHAMANI

IPC: G02B21/00 ,  G06T7/187 ,  G06T7/174 ,  G06T7/11 ,  G06N3/08 ,  G06N3/04 ,  G06N20/20

Abstract: A computing device, method, system, and instructions in a non-transitory computer-readable medium for performing image analysis on 3D microscopy images to predict localization and/or labeling of various structures or objects of interest, by predicting the location in such images at which a dye or other marker associated with such structures would appear. The computing device, method, and system receives sets of 3D images that include unlabeled images, such as transmitted light images or electron microscope images, and labeled images, such as images captured with fluorescence tagging. The computing device trains a statistical model to associate structures in the labeled images with the same structures in the unlabeled light images. The processor further applies the statistical model to a new unlabeled image to generate a predictive labeled image that predicts the location of a structure of interest in the new image.

公开(公告)号：US20230341329A1

公开(公告)日：2023-10-26

申请号：US18005077

申请日：2021-07-28

Applicant: ALLEN INSTITUTE

Inventor： Gregory JOHNSON ,  Chawin OUNKOMOL ,  Forrest COLLMAN ,  Sharmishtaa SESHAMANI ,  Nathalie GAUDREAULT ,  Calysta YAN ,  Jianxu CHEN ,  Susanne RAFELSKI

IPC: G01N21/64

CPC classification number: G01N21/6458 ,  G01N2201/1296 ,  G01N2500/10

Abstract: The present invention provides various methods for screening one or more compounds, suitably using non-invasive visual methods and neural networks for generating predicted fluorescence images of cells, to assess an effect of the compound on the cell, as well as to classify a compound or to determine an activity of a compound. Also provided are systems and methods for carrying out such assessments.

公开(公告)号：US20230281825A1

公开(公告)日：2023-09-07

申请号：US18170076

申请日：2023-02-16

Applicant: ALLEN INSTITUTE

Inventor： Gregory JOHNSON ,  Chawin OUNKOMOL ,  Forrest COLLMAN ,  Sharmishtaa SESHAMANI

IPC: G06T7/11 ,  G06T7/187 ,  G06T7/174 ,  G06N20/20 ,  G02B21/00 ,  G06N3/08 ,  G06N3/045 ,  G06V10/25 ,  G06V10/764 ,  G06V10/50 ,  G06V20/69

CPC classification number: G06T7/11 ,  G06T7/187 ,  G06T7/174 ,  G06N20/20 ,  G02B21/008 ,  G06N3/08 ,  G06N3/045 ,  G06V10/25 ,  G06V10/764 ,  G06V10/50 ,  G06V20/695 ,  G06V20/698 ,  G06T2207/10061 ,  G06T2207/10064 ,  G06T2207/30024

Abstract: A computing device, method, system, and instructions in a non-transitory computer-readable medium for performing image analysis on 3D microscopy images to predict localization and/or labeling of various structures or objects of interest, by predicting the location in such images at which a dye or other marker associated with such structures would appear. The computing device, method, and system receives sets of 3D images that include unlabeled images, such as transmitted light images or electron microscope images, and labeled images, such as images captured with fluorescence tagging. The computing device trains a statistical model to associate structures in the labeled images with the same structures in the unlabeled light images. The processor further applies the statistical model to a new unlabeled image to generate a predictive labeled image that predicts the location of a structure of interest in the new image.